China’s bioenergy potential will be stable and decoupling from economy and population at national level: A study based on machine regression prediction model

Abstract

Policymakers and industry participants strongly demand accurate and convenient methods for predicting bioenergy potential. To address the limitations of existing biophysical models, which require complex inventories and technical support, this study utilizes readily available economic and population data from 1978 to 2021 as independent variables, with bioenergy as the dependent variable. After evaluating ten classical machine learning models and six newly published optimization algorithms, the hybrid of Back Propagation and Marine Predators Algorithm was selected as an effective bioenergy regression prediction model. The prediction results of 2022–2050 indicate that China’s bioenergy potential will reach 13 ± 3.8 Bt equivalent of standard coal and remain stable, decoupled from economic and population trends at the national level over the next three decades. Additionally, developing measures to promote the conversion of biomass into hydrogen, methanol, and sustainable aviation fuels will be a significant opportunity for the sustainable development of the bioenergy industry